#Load Libraries
library(tidyverse)
## ── Attaching packages ────────────────────────────────────────────── tidyverse 1.3.0 ──
## ✓ ggplot2 3.2.1 ✓ purrr 0.3.3
## ✓ tibble 2.1.3 ✓ dplyr 0.8.4
## ✓ tidyr 1.0.2 ✓ stringr 1.4.0
## ✓ readr 1.3.1 ✓ forcats 0.4.0
## ── Conflicts ───────────────────────────────────────────────── tidyverse_conflicts() ──
## x dplyr::filter() masks stats::filter()
## x dplyr::lag() masks stats::lag()
#Load Files
SNPs<- read.table("23andMe_complete.txt", header = TRUE, sep = "\t")
#Adjust Figure Size
SNPs$chromosome=ordered(SNPs$chromosome,levels=c(seq(1,22),"X","Y","MT"))
ggplot(data=SNPs)+
geom_bar(mapping=aes(x=genotype,fill=chromosome))+
coord_polar()+
ggtitle("Total SNPs for each genotype")+
ylab("Total number of SNPs")+
xlab("Genotype")
#Plot graph to a pdf outputfile
pdf("SNP_example_plot.pdf", width=6, height=3)
ggplot(data=SNPs) +
geom_bar(mapping=aes(x=chromosome, fill=genotype))
dev.off()
## quartz_off_screen
## 2
#Plot graph to a png outputfile
ppi <- 300
png("SNP_example_plot.png", width=6*ppi, height=6*ppi, res=ppi)
ggplot(data=SNPs)+
geom_bar(mapping=aes(x=chromosome, fill=genotype))
dev.off
## function (which = dev.cur())
## {
## if (which == 1)
## stop("cannot shut down device 1 (the null device)")
## .External(C_devoff, as.integer(which))
## dev.cur()
## }
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## <environment: namespace:grDevices>
#Rmarkdown loading images #Alternative way using html
#Interactive graphs and tables in RMarkdown reports #Version 1
library(plotly)
##
## Attaching package: 'plotly'
## The following object is masked from 'package:ggplot2':
##
## last_plot
## The following object is masked from 'package:stats':
##
## filter
## The following object is masked from 'package:graphics':
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## layout
p<-ggplot(data=iris, aes(x=Sepal.Length, y=Sepal.Width, color=Species))+
geom_point()
ggplotly(p)
#Version 2
library(plotly)
ggplotly(
ggplot(data=iris,aes(x=Sepal.Length, y=Sepal.Width, color=Species))+
geom_point()
)
#InteractiveTable
library(DT)
datatable(iris)
#Exercise1
SNPs<- read.table("23andMe_complete.txt", header = TRUE, sep="\t")
p<-ggplot(SNPs,aes(chromosome))+
geom_bar(fill="blue")+
ggtitle("Total SNPs for Each Chromosome")+
ylab("SNP count")+
xlab("Chromosome")
p
#Exercise2
mycolor<-c("AA"="blue", "AC"="blue", "AG"="blue", "AT"="blue", "CC"="blue", "CG"="blue", "CT"="blue", "GG"="blue", "GT"="blue", "TT"="blue","A"="pink", "C"="pink", "G"="pink", "T"="pink", "D"="orange", "DD"="orange", "DI"="orange","I"="orange","II"="orange","--"="green")
ggplot(SNPs, aes(chromosome, fill = genotype))+
geom_bar(color = "black")+
ggtitle("Total SNPs count for each chromosome")+
ylab("SNPs count")+
xlab("Type of Chromosome")+
scale_fill_manual(values=c(mycolor))
#Exercise3
ppi <- 300
png("Lab3_Exercise5_plot.png", width=6*ppi, height=6*ppi, res=ppi)
ggplot(data=SNPs,aes(chromosome,fill=genotype))+
geom_bar(position="dodge")
dev.off()
## quartz_off_screen
## 2
#Exercise4
SNPs$chromosome=ordered(SNPs$chromosome, levels=c(seq(1,22),"X","Y","MT"))
ggplot(SNPs,aes(chromosome,fill=genotype))+
geom_bar(position="dodge")+
facet_wrap(~chromosome, scales="free")+
ggtitle("SNP Count for Each Type of Chromosome")+
ylab("SNP Count(Thousands)")+
xlab("Type of Chromosome")
#Exercise5
library(plotly)
SNPs$chromosome=ordered(SNPs$chromosome, levels=c(seq(1,22),"X","Y","MT"))
ggplotly(
ggplot(SNPs,aes(chromosome,fill=genotype))+
geom_bar(position="dodge")+
facet_wrap(~genotype, ncol=2)
)
#Exercise 6
library(DT)
chromosome_subset<-subset(SNPs, chromosome=="Y")
datatable(chromosome_subset)
## Warning in instance$preRenderHook(instance): It seems your data is too big
## for client-side DataTables. You may consider server-side processing: https://
## rstudio.github.io/DT/server.html